Digital Signal Processing (DSP), Sound and Imaging Processing

This is an outstanding and often overlooked book on optimal signal processing. The author does an excellent job relating the filtering problem to optimization in linear spaces and then shows how this is related to the optimal correlation canceller. This approach is justified since correlation cancelling is the fundamental principle underlying nearly all adaptive filtering algorithms. The author often explains concepts from more than one point of view which adds to depth of understanding.

Signal processing is ubiquitous in modern technology. Its mathematical basis and many areas of application are the subject of this book, based on a series of graduate-level lectures held at the Mathematical Sciences Research Institute. Emphasis is on current challenges, new techniques adapted to new technologies, and certainrecent advances in algorithms and theory.

This book describes the essential tools and techniques of statistical signal processing. At every stage theoretical ideas are linked to specific applications in communications and signal processing. The book begins with a development of basic probability, random objects, expectation, and second order moment theory followed by a wide variety of examples of the most popular random process models and their basic uses and properties. Specific applications to the analysis of random signals and systems for communicating, estimating, detecting, modulating, and other processing of signals are interspersed throughout the book.

Digital filters, together with signal processing, are being employed in the new technologies and information systems, and are implemented in different areas and applications. Digital filters and signal processing are used with no costs and they can be adapted to different cases with great flexibility and reliability.

Digital signal processing (DSP) covers a wide range of applications in which the implementation of high-performance systems to meet stringent requirements and performance constraints is receiving increasing attention both in the industrial and academic contexts.

This book presents a thorough introduction to the mathematical foundations of signal and image processing using Fourier and Wavelet Transforms.

Window Functions - otherwise known as weighting functions, tapering functions, or apodization functions―are mathematical functions that are zero-valued outside the chosen interval. They are well established as a vital part of digital signal processing. This book presents an exhaustive and detailed account of window functions and their applications in signal processing, focusing on the areas of digital spectral analysis, design of FIR filters, pulse compression radar, and speech signal processing.

This comprehensive and engaging textbook introduces the basic principles and techniques of signal processing, from the fundamental ideas of signals and systems theory to real-world applications. Students are introduced to the powerful foundations of modern signal processing, including the basic geometry of Hilbert space, the mathematics of Fourier transforms, and essentials of sampling, interpolation, approximation and compression.

Digital signals place great demands on processing power, network bandwidth, storage capacity, I/O speed, and software design. As a result, signal computing is a great laboratory for exercising the full range of knowledge of computer science.

Mixed-signal processing implies the use of both analog and digital in the same system; this is a specialized type of signal processing that requires a high level of experience and training. Knowledge of digital signal processing (DSP) techniques is now becoming a requirement of almost every engineer.

Combines both the DSP principles and real-time implementations and applications, and now updated with the new eZdsp USB Stick, which is very low cost, portable and widely employed at many DSP labs.

This book differs from the classical DSP book model pioneered by O/S. Includes chapters on DFT, Z-Transform and Filter Design. The book starts out with what one reviewer calls "fun topics", and DSP applications.

Signals convey information. Systems transform signals. This book introduces the mathematical models used to design and understand both. It is intended for students interested in developing a deep understanding of how to digitally create and manipulate signals to measure and control the physical world and to enhance human experience and communication.

This open access book provides a detailed introduction to continuous-time and discrete-time signals and systems, with a focus on both theory and applications. Many worked-through examples are provided.

This book is designed to show how many of the mathematical tools the reader knows can be used to understand and employ signal processing techniques in an applied environment. Assuming an advanced undergraduate or graduate-level understanding of mathematics-including familiarity with Fourier series, matrices, probability, and statistics.